Our Research Principle - To solve the algorithmic complexity problems in advanced control system design with unconventional sophisticated methods of computational intelligence

Our Goals - The first theoretical purpose of the Quantum & Soft Computational Intelligence is the development of the Platform background for the design of Integrated Fuzzy Intelligent Control Systems and a research release targeted at sophisticated developers for education, design and experimentation with new types of robust control systems. Quantum Computational Intelligence implements basically a hierarchical quantum strategy of decision making patterned after the soft computing applications. In the important particular case, computational complexity problems in advanced control (unsolved principally by classical algorithms) are solved. For example, the design of a global robustness of advanced control system in unpredicted control situations is achieved owing to application of on-line quantum strategy of decision making relative to quantum knowledge. In advanced control system the achievement of this result with classical random search and adaptive learning algorithms is impossible.

The second theoretical and applied purposes are the know-how implementation of the following control performance: (i) ensure the requested level of intelligent control robustness in unpredicted control situations with knowledge base self-organization using the min-entropy principle of quantum knowledge; and (ii) support the reliability of advanced control systems in conditions of industrial disturbances with optimal thermodynamic trade-off between stability, controllability and robustness.

Quantum control algorithm of knowledge base self-organization that has developed for the task solution in item (i) is the background for the industrial applications of the optimal trade-off solutions in item (ii).

The third applied purpose is a development of flexible Toolkit which can be used on problems that, generally speaking, involve the design of robust wise intelligent control in uncertain complex data and unpredicted control situations. Toolkit has programmable realization on classical computer including sophisticated fast algorithms simulation of quantum algorithms with optimal spatio-temporal computational complexity.

The fourth applied purpose is the design principle realization of robust intelligent control: Development of industrial wise intelligent controllers with physically realized simple structure for complex control objects in unpredicted control situations.

Background for the realization of abovementioned goals and industrial applications is the R&D results of our information design technology.

Information Design Technology developed by our group is based on unconventional methods of computational intelligence and intelligent control systems (link overview). It is committed to creating and supporting an open, collaborative community of companies, universities and individuals interested in working and education on Integrated Fuzzy Intelligent Control Systems. Concurrent with the Quantum & Soft Computation Intelligence Platform release, R&D Group also has launched developer community tools and learning (training) documents.

Commercial Situation The second generation of Soft Computation Intelligence with SW and Toolkit Platform for Simulation Design of Robust Knowledge Base in Integrated Fuzzy Intelligent Control Systems is now available and can be adopted for concrete customer situations.

Business Program Development for Computer Aiding Engineering System - Applied Toolkit: Soft & Quantum Computing Optimizers of Robust KB as Platform for Information Design Technology of Robust Integrated Fuzzy Intelligent Control Systems